Selective Segmentation for Global Optimization of Depth Estimation in Complex Scenes
Joint Authors
Liu, Sheng
Zhai, Binbin
Zhan, Ye
Jin, Haiqiang
Mao, Xiaojun
Feng, Xiaofei
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-14
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
This paper proposes a segmentation-based global optimization method for depth estimation.
Firstly, for obtaining accurate matching cost, the original local stereo matching approach based on self-adapting matching window is integrated with two matching cost optimization strategies aiming at handling both borders and occlusion regions.
Secondly, we employ a comprehensive smooth term to satisfy diverse smoothness request in real scene.
Thirdly, a selective segmentation term is used for enforcing the plane trend constraints selectively on the corresponding segments to further improve the accuracy of depth results from object level.
Experiments on the Middlebury image pairs show that the proposed global optimization approach is considerably competitive with other state-of-the-art matching approaches.
American Psychological Association (APA)
Liu, Sheng& Jin, Haiqiang& Mao, Xiaojun& Zhai, Binbin& Zhan, Ye& Feng, Xiaofei. 2013. Selective Segmentation for Global Optimization of Depth Estimation in Complex Scenes. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1033389
Modern Language Association (MLA)
Liu, Sheng…[et al.]. Selective Segmentation for Global Optimization of Depth Estimation in Complex Scenes. The Scientific World Journal No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1033389
American Medical Association (AMA)
Liu, Sheng& Jin, Haiqiang& Mao, Xiaojun& Zhai, Binbin& Zhan, Ye& Feng, Xiaofei. Selective Segmentation for Global Optimization of Depth Estimation in Complex Scenes. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1033389
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1033389